We present results and analyses from the third VoicePrivacy Challenge held in 2024, which focuses on advancing voice anonymization technologies. The task was to develop a voice anonymization system for speech data that conceals a speaker's voice identity while preserving linguistic content and emotional state. We provide a systematic overview of the challenge framework, including detailed descriptions of the anonymization task and datasets used for both system development and evaluation. We outline the attack model and objective evaluation metrics for assessing privacy protection (concealing speaker voice identity) and utility (content and emotional state preservation). We describe six baseline anonymization systems and summarize the innovative approaches developed by challenge participants. Finally, we provide key insights and observations to guide the design of future VoicePrivacy challenges and identify promising directions for voice anonymization research.

翻译：本文介绍了2024年举办的第三届VoicePrivacy挑战赛的结果与分析，该赛事致力于推动语音匿名化技术的发展。本次任务旨在开发一种针对语音数据的匿名化系统，该系统需在隐藏说话者语音身份的同时，保留其语言内容与情感状态。我们对挑战赛框架进行了系统性概述，包括对匿名化任务、以及用于系统开发与评估的数据集的详细描述。我们阐述了用于评估隐私保护（隐藏说话者语音身份）与实用性（内容与情感状态保留）的攻击模型与客观评价指标。我们描述了六种基线匿名化系统，并总结了挑战赛参与者所开发的创新方法。最后，我们提供了关键见解与观察，以指导未来VoicePrivacy挑战赛的设计，并指出了语音匿名化研究中有前景的发展方向。